Effect of Modified Water‐Bath Method on Microstructure and Mechanical Properties of Wire Arc Additive Manufactured Low‐Carbon Low‐Alloy Steel
Bibliographic record
Abstract
Of late, wire arc additive manufacturing (WAAM) is extensively used in the aerospace and automotive fields to produce large complex metallic components. The water‐bath method is applied for active cooling to address the heat accumulation problem in WAAM. Herein, the modified water‐bath method with a changing level is used to realize different phase transformations, and the microstructure and mechanical properties of the sample are investigated. Heat accumulation in the sample is eliminated using the modified water‐bath method. Furthermore, the microstructure of the fabricated sample shows a mixture of polygonal ferrite (PF), upper bainite (UB), and lath bainite (LB). Layer bands are formed in the entire sample, except in the final layer, and equiaxed ferrite (EF) and an increased fraction of PF appear in these zones. The microhardness and tensile property are enhanced due to the fine LB. The considerable difference in the microhardness between LB and PF causes an obvious wave of hardness, and the tensile property along the horizontal direction is better than the vertical. This study is expected to help broaden the application of the water bath in the microstructure control.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".